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Learning Elasticsearch

You're reading from   Learning Elasticsearch Structured and unstructured data using distributed real-time search and analytics

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787128453
Length 404 pages
Edition 1st Edition
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Author (1):
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Abhishek Andhavarapu Abhishek Andhavarapu
Author Profile Icon Abhishek Andhavarapu
Abhishek Andhavarapu
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Elasticsearch FREE CHAPTER 2. Setting Up Elasticsearch and Kibana 3. Modeling Your Data and Document Relations 4. Indexing and Updating Your Data 5. Organizing Your Data and Bulk Data Ingestion 6. All About Search 7. More Than a Search Engine (Geofilters, Autocomplete, and More) 8. How to Slice and Dice Your Data Using Aggregations 9. Production and Beyond 10. Exploring Elastic Stack (Elastic Cloud, Security, Graph, and Alerting)

Concurrency

We discussed before that an update operation has to first retrieve the old document, apply the changes, and re-index the document. Between retrieving the old document and re-indexing the document, if some other operation updates the document, you would potentially overwrite the change. To solve this problem, Elasticsearch increments the version of the document on each operation.

If the version of the document has been changed between the document retrieval and re-indexing, the index operation fails. Let's take an example:

POST chapter4/person/2/_update 
{
"doc" : {
"name" : "name update 3"
}
}

The response to the preceding operation is as follows:

{
"_index": "chapter4",
"_type": "person",
"_id": "2",
"_version": 4,
"result": "updated&quot...
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